Evolutionary Process for Engineering Optimization in Manufacturing Applications: Fine Brushworks of Single-Objective to Multi-Objective/Many-Objective Optimization

Abstract

Single-objective to multi-objective/many-objective optimization (SMO) is a new paradigm in the evolutionary transfer optimization (ETO), since there are only “1 + 4” pioneering works on SMOs so far, that is, “1” is continuous and is firstly performed by Professors L. Feng and H.D. Wang, and “4” are firstly proposed by our group for discrete cases. As a new computational paradigm, theoretical insights into SMOs are relatively rare now. Therefore, we present a proposal on the fine brushworks of SMOs for theoretical advances here, which is based on a case study of a permutation flow shop scheduling problem (PFSP) in manufacturing systems via lenses of building blocks, transferring gaps, auxiliary task and asynchronous rhythms. The empirical studies on well-studied benchmarks enrich the rough strokes of SMOs and guide future designs and practices in ETO based manufacturing scheduling, and even ETO based evolutionary processes for engineering optimization in other cases.

Decomposition Is All You Need: Single-Objective to Multi-Objective Optimization towards Artificial General Intelligence

“…The most related work to our paper here is [5]. To the best of their knowledge, their paper was the first paper (they did not use the concept In the background of industrial intelligence [1,2], the lantern is derived from the tree, and the tree is rooted in the "Tai ji" [2] (the same as [7]). As Chinese lanterns symbolize red ornaments for a festive atmosphere, the lantern above is dedicated to the establishment of our lab at the Frontier Science Center for Industrial Intelligence and System Optimization, Ministry of Education, established since 2021, which is a national-level center.…”

“…Artificial general intelligence [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] (AGI) for language and vision includes the wellknown Chat GPT and ViT, respectively. Both Chat GPT and ViT are empowered by Transformers.…”

“…The works on SMO by our groups can be "gathered" together in a Chinese lantern diagram (Figure 1) as follows: the conference paper of "Meets", future works named as "xMeets" and journal papers of "iMeets" [7], "rMeets" [8], and "eMeets". Actually, eMeets is this paper here and is an extension of Meets [6], thus inheriting the originality status of Meets.…”

Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization

“…Optimization is described as the process of determining the most suitable values for the parameters of a problem with the goal to obtain the ideal solution 1 . Optimization Algorithms have gained acknowledgment as effective instruments for improving various types of single-objective, multi-objective, and many-objective problems 2 .…”